Genomic selection (GS) is an advanced breeding technique which associates the genotype and phenotype of a training population to make predictions about the breeding value of related individuals based on genotypic information alone. This technique potentially improves breeding efficacy by reducing confounding environmental variables, allowing strong selection on traits that are otherwise difficult to phenotype and reducing the duration of the breeding cycle.
This project aims to implement GS on a strawberry breeding programme based at NIAB EMR, with particular focus on ensuring commercial viability of the developed technologies. This project is split into 4 work packages:
- Development of a cost-effective, scalable genotyping system suitable for a strawberry breeding population
Development of a high-throughput 3D image based strawberry phenotyping system
Investigation into statistical techniques for GS using a bi-parental strawberry mapping population
Deployment and validation of GS on a commercial strawberry breeding population.
- Publications: He, Joe Q., Richard J. Harrison, and Bo Li. 2017. “A Novel 3D Imaging System for Strawberry Phenotyping.” Plant Methods 13(1):93.
PhD student: Joe He
PhD supervisor: Richard Harrison
Duration: Oct 2016 – Oct 2019